Queue management method and device, computer device and storage medium

Abstract

The application relates to a queuing management method and device, computer equipment and a computer readable storage medium. The execution speed of the current task of each queue is determined based on the task execution data of each queue in a preset queuing area. The task execution data of each queue in the preset queuing area is obtained from a video collected for the preset queuing area. The current queuing quantity of each queue is determined, and the current queuing waiting time of each queue is determined according to the current queuing quantity of each queue and the execution speed of the current task of each queue. The number of queues that need to be adjusted and the corresponding number of objects that need to be adjusted are determined according to the current queuing waiting time of each queue, and the queues that need to be adjusted are instructed to make corresponding adjustments. The queuing situation of all queues is automatically analyzed and managed based on a video monitoring technology, the queuing time of each queue is balanced, the queuing time of a certain queue is prevented from being too long, and thus the experience of individuals in the queuing process is effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, in particular to a queuing management method and device, computer equipment and storage medium. BACKGROUND

[0002] In supermarkets, amusement parks and other shopping places, etc., queuing is often needed, and usually multiple queues are simultaneously queued. However, due to various reasons, some queues are digested relatively quickly, while some queues are digested relatively slowly, so that some individuals have a long queuing waiting time.

[0003] In the prior art, individuals in a queue with a long queuing time need to make self-observation to adjust the queue, so as to avoid a long queuing time. The reference basis for self-observation by individuals is generally the length of the queue, and inaccurate judgment often occurs, which leads to a serious impact on individual experience in the queuing process of the prior art. SUMMARY

[0004] Therefore, it is necessary to provide a queuing management method, device, computer equipment and computer readable storage medium to solve the problem of a serious impact on individual experience in the queuing process in the related art.

[0005] In a first aspect, the embodiments of the present application implement a queuing management method, which comprises the following steps:

[0006] Based on task execution data of each queue in a preset queuing area, the execution speed of the current task of each queue is determined; the task execution data of each queue in the preset queuing area is obtained from a video collected for the preset queuing area;

[0007] The current queuing quantity of each queue is determined, and the current queuing waiting time of each queue is determined according to the current queuing quantity of each queue and the execution speed of the current task of each queue;

[0008] According to the current queuing waiting time of each queue, the queue that needs to be adjusted and the quantity of corresponding objects that need to be adjusted are determined, and the queue that needs to be adjusted is instructed to make corresponding adjustment.

[0009] In one of the embodiments, the determination of the current queuing quantity of each queue comprises the following steps:

[0010] The video collected for the preset queuing area is detected for queuing objects to determine the current queuing quantity of each queue.

[0011] In one of the embodiments, the determination of the queue that needs to be adjusted and the quantity of corresponding objects that need to be adjusted according to the current queuing waiting time of each queue comprises the following steps:

[0012] calculating an average queuing waiting time of all the queues according to the current queuing waiting time of each queue;

[0013] determining the queue needing adjustment based on the deviation between the current queuing waiting time of each queue and the average queuing waiting time, and determining the number of objects needing adjustment of the queue needing adjustment according to the deviation between the current queuing waiting time of the queue needing adjustment and the average queuing waiting time and the execution speed of the current task of the queue needing adjustment.

[0014] In one embodiment, the determining the queue needing adjustment based on the deviation between the current queuing waiting time of each queue and the average queuing waiting time comprises the following steps:

[0015] comparing the deviation between the current queuing waiting time of each queue and the average queuing waiting time with a set threshold value, and determining the current queue as the queue needing adjustment if the deviation between the current queuing waiting time of the current queue and the average queuing waiting time exceeds the set threshold value.

[0016] In one embodiment, the determining the queue needing adjustment and the number of objects needing adjustment of the queue needing adjustment according to the current queuing waiting time of each queue, and instructing the queue needing adjustment to make corresponding adjustment comprises the following steps:

[0017] presetting an adjustment period;

[0018] determining the queue needing adjustment and the number of objects needing adjustment of the queue needing adjustment according to the current queuing waiting time of each queue every time the adjustment period passes, and instructing the queue needing adjustment to make corresponding adjustment.

[0019] In one embodiment, the instructing the queue needing adjustment to make corresponding adjustment comprises the following steps:

[0020] instructing the queue needing adjustment to make corresponding adjustment by voice broadcast.

[0021] In one embodiment, the method further comprises:

[0022] updating the execution speed of the current task of each queue in real time.

[0023] In a second aspect, the embodiments of the present application implement a queuing management device, which comprises a determining module, a calculating module and an adjusting module.

[0024] The determining module is used to determine the execution speed of the current task of each queue based on the task execution data of each queue within a preset queuing area; the task execution data of each queue within the preset queuing area is obtained from video collected for the preset queuing area.

[0025] The calculation module is used to determine the current queue size of each queue, and to determine the current queuing time of each queue based on the current queue size and the execution speed of the current task in each queue.

[0026] The adjustment module is used to determine the queues that need to be adjusted and the number of objects to be adjusted according to the current queuing time of each queue, and instruct the queues that need to be adjusted to make the corresponding adjustments.

[0027] Thirdly, this embodiment provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0028] Fourthly, this embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0029] This application determines the current task execution speed of each queue within a preset queuing area by acquiring task execution data from video footage collected from that area. Based on this data, and considering the current number of people in each queue, the application determines the current queuing time. Finally, based on the current queuing time, the application identifies the queues requiring adjustment and the corresponding number of items to be adjusted, instructing those queues to make the necessary adjustments. This automated analysis and management of all queues' queuing status using video surveillance technology balances the queuing time of each queue, preventing excessively long queue times and effectively improving the individual's queuing experience. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0031] Figure 1 This is an application scenario diagram of the queue management method provided in the embodiments of this application;

[0032] Figure 2 This is a flowchart of the queuing management method provided in the embodiments of this application.Figure 1 ;

[0033] Figure 3 This is a flowchart of the queuing management method provided in the embodiments of this application. Figure 2 ;

[0034] Figure 4 A schematic diagram of the queuing management device provided in the embodiments of this application;

[0035] Figure 5 A schematic diagram of the structure of a computer device provided in the embodiments of this application. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0037] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0038] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0039] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0040] Figure 1 This is a diagram illustrating an application scenario of a queue management method provided in one embodiment of this application. Figure 1 As shown, server 101 and monitoring terminal 102 can transmit data via a network. The field of view of monitoring terminal 102 covers a preset queuing area. Monitoring terminal 102 is used to capture video of the preset queuing area and transmit the captured video to server 101. Server 101 obtains task execution data for each queue within the preset queuing area from the video captured, and determines the execution speed of the current task for each queue based on the task execution data. Server 101 also determines the current number of people in each queue and, based on the current number of people in each queue and the execution speed of the current task, determines the current waiting time for each queue. Finally, based on the current waiting time for each queue, server 101 determines the queues that need adjustment and the corresponding number of objects to be adjusted, and instructs the queues that need adjustment to make the corresponding adjustments. Server 101 can be implemented by a standalone server or a server cluster composed of multiple servers, and monitoring terminal 102 can be implemented by any video capture device.

[0041] This embodiment provides a queue management method, such as Figure 2 As shown, the method includes the following steps:

[0042] Step S210: Based on the task execution data of each queue within the preset queuing area, determine the execution speed of the current task in each queue; the task execution data of each queue within the preset queuing area is obtained from the video collected for the preset queuing area.

[0043] Specifically, the preset queuing area can be any location where tasks need to be performed, and there may be more than one queue within the preset queuing area, such as supermarket checkouts, amusement park ticket counters, highway toll booths, train station baggage checkpoints, and nucleic acid testing sites. By collecting video footage from the preset queuing area, task execution data for each queue within the preset queuing area can be obtained, including the execution time and specific details of each queue's tasks, thus determining the current task execution speed for each queue. For example, based on the task execution data for each queue within the preset queuing area, if the task of the last queued object processed by a certain queue before the current time took 2 minutes, then 2 (min / object) can be taken as the current task execution speed for that queue. Of course, to obtain a more accurate current task execution speed for each queue, the average time taken for the tasks of the last preset number of queued objects processed by each queue before the current time can be used as the current task execution speed for each queue.

[0044] Step S220: Determine the current queue size for each queue, and determine the current queuing time for each queue based on the current queue size and the execution speed of the current task in each queue.

[0045] Specifically, those entering the queuing area for task processing typically choose their own queue. Therefore, the current queue size varies. This can be determined by setting a counter at the entrance of each queue, with an initial value of 0. Each time a queued object enters from the back of the queue, the counter value is incremented by 1; each time a queued object leaves from the front, the counter value is decremented by 1. The current queue size is determined by obtaining the counter value for each queue. As one implementation method, queuing objects can also be detected in the video captured of the preset queuing area to determine the current queue size. Of course, other methods can also be used to determine the current queue size.

[0046] After determining the current number of people in each queue, the current queuing time for each queue can be determined based on the current number of people in each queue and the current execution speed of the tasks in each queue. For example, assuming that a queue has 10 people in it, and the current execution speed of the tasks in that queue is determined to be 2 (min / task) according to step S210, then the current queuing time for that queue can be determined to be 20 minutes.

[0047] Step S230: Based on the current queuing time of each queue, determine the queues that need to be adjusted and the corresponding number of objects to be adjusted, and instruct the queues that need to be adjusted to make the corresponding adjustments.

[0048] Since the current queuing times of different queues vary, the queues that need adjustment and the number of objects requiring adjustment can be determined based on the current queuing time of each queue. Specifically, to balance the current queuing times of each queue, the queues with longer and shorter current queuing times can be identified as the queues that need adjustment, and the queues with longer current queuing times can be moved to the queues with shorter current queuing times. Furthermore, to ensure fairness, the queues at the end of the queues with longer current queuing times can be moved to the end of the queues with shorter current queuing times. The number of objects requiring adjustment can be determined by considering the queuing times of the queues with longer and shorter current queuing times. For example, suppose there are 6 queues in the queuing area, and the current queuing time for each queue is 40 minutes, 21 minutes, 27 minutes, 30 minutes, 10 minutes, and 22 minutes. Then, the first and fifth queues can be identified as the queues that need to be adjusted. The queuing time difference between the first and fifth queues is 30 minutes. The number of objects that need to be adjusted can be determined by combining the number of tasks that can be executed in the first queue within 15 minutes and the number of tasks that can be executed in the fifth queue within 15 minutes. Based on the determined number of objects that need to be adjusted, the objects at the end of the first queue are moved to the end of the fifth queue.

[0049] As one implementation method, the average queuing time of all queues can be calculated based on the current queuing time of each queue; based on the deviation between the current queuing time of each queue and the average queuing time, the queues that need to be adjusted are determined, and based on the deviation between the current queuing time of the queues that need to be adjusted and the average queuing time, as well as the execution speed of the current task of the queues that need to be adjusted, the number of objects to be adjusted for the queues that need to be adjusted is determined.

[0050] Specifically, taking a queuing area with six queues as an example, the current waiting times for each queue are 40 minutes, 21 minutes, 27 minutes, 30 minutes, 10 minutes, and 22 minutes. Therefore, the average waiting time for all queues is 25 minutes. The deviations between the current waiting time of each queue and the average waiting time are 15 minutes, 4 minutes, 2 minutes, 5 minutes, 15 minutes, and 3 minutes, respectively. Since each queue deviates from the average waiting time, all queues can be identified as those requiring adjustment. Furthermore, the deviation between the first queue and the average waiting time is 15 minutes. Assuming the current task execution rate of the first queue is 3 (min / task), then 5 items need to be moved out of the first queue. The deviation between the second queue and the average waiting time is 4 minutes. Assuming the current task execution rate of the second queue is 2 (min / task), then 2 items need to be moved in of the second queue. The deviation between the third queue and the average waiting time is 2 minutes. Assuming the current task execution rate of the third queue is 3 (min / task), then 1 item needs to be moved out of the third queue. The deviation between the fourth queue and the average waiting time is... The deviation between the waiting times is 5 minutes. Assuming the current task execution speed of the fourth queue is 2 (min / task), then the number of objects to be adjusted in the fourth queue is 3 to be moved out. The deviation between the fifth queue and the average waiting time is 15 minutes. Assuming the current task execution speed of the fifth queue is 2.5 (min / task), then the number of objects to be adjusted in the fifth queue is 6 to be moved in. The deviation between the sixth queue and the average waiting time is 3 minutes. Assuming the current task execution speed of the sixth queue is 3 (min / task), then the number of objects to be adjusted in the sixth queue is 1 to be moved in. Then, according to the needs of each queue, each queue is instructed to make the corresponding adjustments.

[0051] Of course, it is inevitable that the total number of objects to be retrieved from all queues will not be equal to the total number of objects to be retrieved from all queues. In this case, the queued objects can be adjusted according to the actual situation to ensure that the queuing time of all queues is maximized and balanced.

[0052] As another implementation method, the deviation between the current queuing time and the average queuing time of each queue can be compared with a set threshold. If the deviation exceeds the set threshold, the current queue is identified as needing adjustment. Taking the above six queues as an example, the current queuing times are 40 minutes, 21 minutes, 27 minutes, 30 minutes, 10 minutes, and 22 minutes, respectively. The average queuing time for all queues is 25 minutes, and the deviations between the current queuing time and the average queuing time for each queue are 15 minutes, 4 minutes, 2 minutes, 5 minutes, 15 minutes, and 3 minutes, respectively. It can be seen that the deviations between the current queuing time and the average queuing time for some queues are very small, such as the third and sixth queues. Since queue adjustments also take time, and the actual speed at which queues execute tasks can vary, a queue doesn't need to be designated as requiring adjustment if the deviation between its current waiting time and average waiting time is small. Only when the deviation exceeds a set threshold is the current queue identified as needing adjustment. This balances the queuing time of each queue while reducing the number of queues requiring adjustment, thus effectively improving queue adjustment efficiency. The threshold can be adjusted according to actual needs.

[0053] In existing technologies, individuals in long queues often adjust their queues based on their own observations to avoid excessively long waiting times. However, the basis for these observations is usually the length of the queue, which often leads to inaccurate judgments. As a result, the queuing process in existing technologies severely impacts the individual's experience.

[0054] To address the aforementioned issues, this application proposes a queue management method. This method determines the current task execution speed of each queue within a preset queuing area based on task execution data obtained from video footage collected from that area. Then, based on the current task execution speed and the current number of people in each queue, the method determines the current waiting time for each queue. Finally, based on the current waiting time, the method identifies the queues requiring adjustment and the corresponding number of items to be adjusted, instructing the queues to make the necessary adjustments. This automated analysis and management of all queues' queuing status using video surveillance technology balances the queuing time of each queue, preventing excessively long queuing times in any particular queue and effectively improving the individual's queuing experience.

[0055] In one embodiment, step S230 above determines the queues that need adjustment and the corresponding number of objects to be adjusted based on the current queuing time of each queue, and instructs the queues that need adjustment to make the corresponding adjustments, including the following steps:

[0056] Step S231: Preset adjustment cycle;

[0057] Step S232: After each adjustment cycle, based on the current queuing time of each queue, determine the queues that need adjustment and the corresponding number of objects to be adjusted, and instruct the queues that need adjustment to make the corresponding adjustments.

[0058] Specifically, because queues are constantly being filled and replaced, the waiting time for each queue is dynamically changing. However, it's impractical to constantly adjust queues, as this would easily lead to queuing chaos and waste server resources for queue management. Conversely, it's also not feasible to only adjust queues once, as this could easily lead to uneven queuing times across queues again. Therefore, in this embodiment, a preset adjustment cycle is used. After each adjustment cycle, based on the current waiting time of each queue, the queues requiring adjustment and the corresponding number of queues needing adjustment are determined, and the queues requiring adjustment are instructed to make the necessary adjustments. This effectively balances the queuing time of each queue while conserving server resources.

[0059] As one implementation method, voice prompts can be used to instruct queues that require adjustment to make the necessary changes. Additionally, the adjustment method for each queue can be displayed on the connected screen, thus instructing the queues requiring adjustment to do so. Furthermore, some queuing areas have corresponding apps or public accounts, and the corresponding adjustment strategies can be pushed to the respective apps or public accounts to instruct the queues requiring adjustment to make the necessary changes.

[0060] In one embodiment, the queue management method further includes the following steps:

[0061] Step S240: Update the execution speed of the current task in each queue in real time.

[0062] Specifically, by updating the execution speed of the current task in each queue in real time, the execution speed of the current task in each queue can be quickly obtained when queue adjustments are needed, thereby adjusting the queues at the fastest speed and effectively improving the efficiency of queue adjustments.

[0063] like Figure 3 As shown, this embodiment also provides a queue management method, which includes the following steps:

[0064] Step S301: Obtain task execution data for each queue from the video collected for the preset queuing area.

[0065] Step S302: Based on the task execution data of each queue within the preset queuing area, determine the execution speed of the current task in each queue.

[0066] Step S303: Determine the current number of people in each queue, and determine the current waiting time for each queue based on the current number of people in each queue and the execution speed of the current task in each queue.

[0067] Step S304: Determine whether the current time has reached the preset adjustment period. If yes, proceed to step S305; otherwise, proceed to step S301.

[0068] Step S305: Calculate the average queuing time for all queues based on the current queuing time of each queue.

[0069] Step S306: Determine whether the deviation between the current queuing time and the average queuing time of each queue exceeds a set threshold. If so, proceed to step S307.

[0070] Step S307: The queues whose current queuing time deviates from the average queuing time by more than a set threshold are identified as queues that need to be adjusted.

[0071] Step S308: Based on the deviation between the current queuing time and the average queuing time of the queue to be adjusted, and the execution speed of the current task of the queue to be adjusted, determine the number of objects to be adjusted in the queue to be adjusted, and instruct the queue to be adjusted to make the corresponding adjustments.

[0072] Figure 4 This is a schematic diagram of a queue management device according to an embodiment of the present invention, such as... Figure 4 The present invention provides a queue management device 30, which includes: a determination module 31, a calculation module 32, and an adjustment module 33;

[0073] The determination module 31 is used to determine the execution speed of the current task of each queue based on the task execution data of each queue in the preset queuing area; the task execution data of each queue in the preset queuing area is obtained from the video collected for the preset queuing area;

[0074] The calculation module 32 is used to determine the current number of people in each queue and, based on the current number of people in each queue and the execution speed of the current task in each queue, to determine the current waiting time in each queue.

[0075] The adjustment module 33 is used to determine the queues that need to be adjusted and the number of objects to be adjusted based on the current queuing time of each queue, and to instruct the queues that need to be adjusted to make the corresponding adjustments.

[0076] The aforementioned queue management device 30 determines the current task execution speed of each queue based on task execution data of each queue within the preset queue area obtained from video footage collected from the preset queue area. It then determines the current waiting time for each queue based on the current task execution speed and the current number of people in each queue. Finally, it determines the queues requiring adjustment and the corresponding number of items to be adjusted based on the current waiting time of each queue, and instructs the queues requiring adjustment to make the necessary adjustments. This allows for automated analysis and management of the queuing situation of all queues based on video surveillance technology, balancing the queuing time of each queue, preventing excessively long queuing times in any particular queue, and effectively improving the individual's experience during the queuing process.

[0077] In one embodiment, the calculation module 32 is further configured to detect queuing objects in the video collected for a preset queuing area and determine the current number of people queuing in each queue.

[0078] In one embodiment, the adjustment module 33 is further configured to calculate the average queuing time of all queues based on the current queuing time of each queue; determine the queues that need adjustment based on the deviation between the current queuing time of each queue and the average queuing time; and determine the number of objects to be adjusted for the queues that need adjustment based on the deviation between the current queuing time of the queues that need adjustment and the average queuing time, and the execution speed of the current task of the queues that need adjustment.

[0079] In one embodiment, the adjustment module 33 is further configured to compare the deviation between the current queuing time and the average queuing time of each queue with a set threshold. If the deviation between the current queuing time and the average queuing time of the current queue exceeds the set threshold, the current queue is determined to be a queue that needs to be adjusted.

[0080] In one embodiment, the adjustment module 33 is also used to preset an adjustment cycle; after each adjustment cycle, based on the current queuing time of each queue, it determines the queues that need to be adjusted and the corresponding number of objects to be adjusted, and instructs the queues that need to be adjusted to make the corresponding adjustments.

[0081] In one embodiment, the adjustment module 33 is also used to instruct the queues that need adjustment to make corresponding adjustments via voice broadcast.

[0082] In one embodiment, the queue management device 30 further includes an update module for real-time updating of the execution speed of the current task in each queue.

[0083] It should be noted that the above modules can be functional modules or program modules, and can be implemented in software or hardware. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or they can be stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0084] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores a set of preset configuration information. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a queuing management method.

[0085] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, a network interface, a display screen, and input devices connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a queuing management method. The display screen of the computer device may be a liquid crystal display (LCD) or an electronic ink display. The input devices of the computer device may be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the casing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0086] Those skilled in the art will understand that Figure 5The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0087] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0088] Based on the task execution data of each queue within the preset queuing area, the execution speed of the current task in each queue is determined; the task execution data of each queue within the preset queuing area is obtained from video collected from the preset queuing area.

[0089] Determine the current number of people in each queue, and based on the current number of people in each queue and the current execution speed of the tasks in each queue, determine the current waiting time for each queue.

[0090] Based on the current queuing time of each queue, determine the queues that need adjustment and the corresponding number of objects to be adjusted, and instruct the queues that need adjustment to make the corresponding adjustments.

[0091] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0092] Based on the task execution data of each queue within the preset queuing area, the execution speed of the current task in each queue is determined; the task execution data of each queue within the preset queuing area is obtained from video collected from the preset queuing area.

[0093] Determine the current number of people in each queue, and based on the current number of people in each queue and the execution speed of the current tasks in each queue, determine the current waiting time for each queue.

[0094] Based on the current queuing time of each queue, determine the queues that need adjustment and the corresponding number of objects to be adjusted, and instruct the queues that need adjustment to make the corresponding adjustments.

[0095] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0096] The system detects queuing objects in the video collected from the preset queuing area and determines the current number of people in each queue.

[0097] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0098] Calculate the average waiting time for all queues based on the current waiting time for each queue.

[0099] Based on the deviation between the current queuing time and the average queuing time of each queue, the queues that need adjustment are determined. Then, based on the deviation between the current queuing time and the average queuing time of the queues that need adjustment, and the execution speed of the current tasks in the queues that need adjustment, the number of objects to be adjusted in the corresponding queues is determined.

[0100] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0101] The deviation between the current queuing time and the average queuing time of each queue is compared with a set threshold. If the deviation between the current queuing time and the average queuing time of the current queue exceeds the set threshold, the current queue is identified as a queue that needs to be adjusted.

[0102] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0103] Preset adjustment cycle;

[0104] After each adjustment cycle, based on the current queuing time of each queue, determine the queues that need adjustment and the corresponding number of objects to be adjusted, and instruct the queues that need adjustment to make the corresponding adjustments.

[0105] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0106] The system uses voice prompts to instruct queues that require adjustment to make the necessary changes.

[0107] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0108] The execution speed of the current task in each queue is updated in real time.

[0109] The aforementioned storage medium determines the execution speed of the current task in each queue based on task execution data of each queue within the preset queuing area obtained from video footage collected from the preset queuing area. It then determines the current queuing time for each queue based on the current task execution speed and the current number of queues. Finally, it determines the queues requiring adjustment and the corresponding number of items to be adjusted based on the current queuing time, and instructs the queues requiring adjustment to make the necessary adjustments. This allows for automated analysis and management of the queuing situation of all queues based on video surveillance technology, balancing the queuing time of each queue, preventing excessively long queuing times in any particular queue, and effectively improving the individual's experience during the queuing process.

[0110] It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application. It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0111] Obviously, the accompanying drawings are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar situations based on these drawings without any creative effort. Furthermore, it is understood that although the work done in this development process may be complex and lengthy, for those skilled in the art, certain design, manufacturing, or production modifications made based on the technical content disclosed in this application are merely conventional technical means and should not be considered as insufficient disclosure of this application.

[0112] The term "embodiment" in this application refers to a specific feature, structure, or characteristic described in connection with an embodiment that may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily imply the same embodiment, nor does it imply that it is mutually exclusive with or independent of other embodiments. It will be clearly or implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0113] The above embodiments merely illustrate several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of patent protection. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims

1. A queue management method, characterized in that, The method includes the following steps: Based on the task execution data of each queue within a preset queuing area, the execution speed of the current task in each queue is determined; the task execution data of each queue within the preset queuing area is obtained from the video collected for the preset queuing area; the execution speed of the current task in each queue is the average time taken for the tasks of the last preset number of queued objects processed by each queue before the current time. Determine the current queue size for each queue, and based on the current queue size and the execution speed of the current task for each queue, determine the current queue waiting time for each queue. Based on the current queuing time of each queue, determine the queues that need adjustment and the corresponding number of objects to be adjusted, and instruct the queues that need adjustment to make the corresponding adjustments. The step of determining the queues that need adjustment and the number of objects to be adjusted based on the current queuing time of each queue includes the following steps: Calculate the average queuing time for all queues based on the current queuing time stated for each queue. The deviation between the current queuing time and the average queuing time of each queue is compared with a set threshold. If the deviation between the current queuing time and the average queuing time of the current queue exceeds the set threshold, the current queue is identified as the queue that needs adjustment. Based on the deviation between the current queuing time and the average queuing time of the queue that needs adjustment and the execution speed of the current task of the queue that needs adjustment, the number of objects to be adjusted in the corresponding queue is determined.

2. The queue management method according to claim 1, characterized in that, Determining the current queue size for each queue includes the following steps: The video collected for the preset queuing area is used to detect queuing objects and determine the current number of people in each queue.

3. The queue management method according to claim 1 or 2, characterized in that, The process of determining the queues requiring adjustment and the corresponding number of items to be adjusted based on the current queuing time of each queue, and instructing the queues requiring adjustment to make the corresponding adjustments, includes the following steps: Preset adjustment cycle; After each adjustment cycle, based on the current queuing time of each queue, the queues that need adjustment and the corresponding number of objects to be adjusted are determined, and the queues that need adjustment are instructed to make the corresponding adjustments.

4. The queue management method according to claim 1, characterized in that, The instruction to adjust the queue that needs adjustment includes the following steps: The system uses voice prompts to instruct the queues that require adjustment to make the necessary adjustments.

5. The queue management method according to claim 1, characterized in that, The method further includes: The execution speed of the current task in each queue is updated in real time.

6. A queue management device, characterized in that, The device includes: a determining module, a calculating module, and an adjusting module; The determining module is used to determine the execution speed of the current task of each queue based on the task execution data of each queue in the preset queuing area; the task execution data of each queue in the preset queuing area is obtained from the video collected for the preset queuing area; the execution speed of the current task of each queue is the average time taken for the tasks of the last preset number of queued objects processed by each queue before the current time. The calculation module is used to determine the current queue size of each queue, and to determine the current queuing time of each queue based on the current queue size and the execution speed of the current task in each queue. The adjustment module is used to determine the queues that need to be adjusted and the number of objects to be adjusted according to the current queuing time of each queue, and instruct the queues that need to be adjusted to make the corresponding adjustments. The step of determining the queues that need adjustment and the corresponding number of objects to be adjusted based on the current queuing time of each queue includes: Calculate the average queuing time for all queues based on the current queuing time stated for each queue. The deviation between the current queuing time and the average queuing time of each queue is compared with a set threshold. If the deviation between the current queuing time and the average queuing time of the current queue exceeds the set threshold, the current queue is identified as the queue that needs adjustment. Based on the deviation between the current queuing time and the average queuing time of the queue that needs adjustment and the execution speed of the current task of the queue that needs adjustment, the number of objects to be adjusted in the corresponding queue is determined.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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